Video inspection systems, such as borescopes, have been widely used for capturing images or videos of difficult-to-reach locations by “snaking” image sensor(s) to these locations. Applications utilizing borescope inspections include aircraft engine blade inspection, power turbine blade inspection, internal inspection of mechanical devices, and the like.
A variety of techniques for inspecting the images or videos provided by borescopes for determining defects therein have been proposed in the past. Most such techniques capture and display images or videos to human inspectors for defect detection and interpretation. Human inspectors then decide whether any defect within those images or videos exists. Other techniques utilize automated inspection techniques for analysis of images or video provided by a borescope.
Once defects are detected in a member of a device, the member must typically be manually located within the device and reinspected to confirm the presence and extent of the defect identified in the images or video. Identifying and locating the defective member within the device may be time-consuming and difficult because of the size of the device, the quantity of members within the device that may need to be sorted through, the location of the defective member within the device, and, in some cases, the similarity of each member to one another. Accordingly, it would be beneficial if an improved technique were developed for controlling the position of members, within a device, for which defects have been detected.